Data-analysis software framework 2DMAT and its application to experimental measurements for two-dimensional material structures

Published: 11 August 2022| Version 1 | DOI: 10.17632/c2t3vzbx9f.1
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Description

An open-source data-analysis framework 2DMAT has been developed for experimental measurements of two-dimensional material structures. 2DMAT offers five analysis methods: (i) Nelder-Mead optimization, (ii) grid search, (iii) Bayesian optimization, (iv) replica exchange Monte Carlo method, and (v) population-annealing Monte Carlo method. Methods (ii) through (v) are implemented by parallel computation, which is efficient not only for personal computers but also for supercomputers. The current version of 2DMAT is applicable to total-reflection high-energy positron diffraction (TRHEPD), surface X-ray diffraction (SXRD), and low-energy electron diffraction (LEED) experiments by installing corresponding forward problem solvers that generate diffraction intensity data from a given dataset of the atomic positions. The analysis methods are general and can be applied also to other experiments and problems.

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Condensed Matter Physics, Computational Physics, Data Analysis, Application of Monte Carlo Method, Bayesian Optimisation

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